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Duration 21 hours
Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The critical role of AI in modern cluster operations
- Constraints of conventional scaling and scheduling logic
- Essential ML concepts for resource management
Core Principles of Kubernetes Resource Management
- Basics of CPU, GPU, and memory allocation
- Navigating quotas, limits, and requests
- Detecting performance bottlenecks and inefficiencies
Machine Learning Strategies for Scheduling
- Supervised and unsupervised models for optimal workload placement
- Algorithms for predicting resource demand
- Incorporating ML features into custom schedulers
Reinforcement Learning for Intelligent Autoscaling
- How RL agents adapt based on cluster behavior
- Constructing reward functions for maximum efficiency
- Developing RL-driven autoscaling frameworks
Predictive Autoscaling via Metrics and Telemetry
- Leveraging Prometheus data for future forecasting
- Applying time-series models to autoscaling processes
- Assessing prediction accuracy and refining models
Deploying AI-Driven Optimization Tools
- Integrating ML frameworks with Kubernetes controllers
- Implementing intelligent control loops
- Enhancing KEDA for AI-assisted decision-making
Cost and Performance Optimization Tactics
- Lowering compute expenses through predictive scaling
- Boosting GPU utilization with ML-driven placement
- Balancing latency, throughput, and overall efficiency
Practical Scenarios and Real-World Applications
- Autoscaling high-load applications using AI
- Optimizing heterogeneous node pools
- Applying ML techniques in multi-tenant environments
Summary and Future Directions
Requirements
- A solid grasp of Kubernetes core concepts
- Hands-on experience with deploying containerized applications
- Proficiency in cluster operations and resource management
Target Audience
- SREs managing large-scale distributed systems
- Kubernetes operators handling high-demand workloads
- Platform engineers focused on optimizing compute infrastructure
Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
basic understanding of container/kubernetes and how they interact features of the openshift plattform
